Irina Mihai and Tekin Mentes present on self-service analytics and data visualization supported by next generation big data architecture at LeasePlan. Irina leads LeasePlan's data visualization practice with over 7 years experience in digital analytics. Tekin is head of data technologies and responsible for LeasePlan's data as a service platform. They discuss LeasePlan's focus on end-to-end services and vehicle lifecycle management as the world's largest fleet management company. Key lessons from their journey implementing self-service analytics include thinking like a product owner, recognizing the value of data as the 5th V of big data, and shifting to modern analytics platforms.

1. SELF-SERVICE
ANALYTICS
DRIVING THE BUSINESS THROUGH DATA VISUALIZATION SUPPORTED
BY NEXT GEN BIG DATA ARCHITECTURE
Irina Mihai & Tekin Mentes, LeasePlan Digital
Big Data Expo
18 September 2019

2. Irina Mihai is a snr. digital analyst and currently leading the data
vizualization practice within LeasePlan Digital.
She has over 7 years of experience in digital analytics across a
variety of industries.
She is passionate about extracting value out of data and steering
business decisions with actionable recommendations.
Irina holds an MSc in Marketing Management from the
Rotterdam School of Management at the Erasmus University and
a BS in International Business from the Vienna University of
Economics.
About us
Tekin Mentes is the head of data technologies.
He is responsible for building LeasePlan’s data as a service
platform where insights create new products and services
through effective and timely exploitation of data assets.
He has over 20-year core experience with a proven track record
of forging solid relationships with strategic partners across
multiple organizational levels.
Tekin holds an executive MBA from Rotterdam School of
Management at the Erasmus University, and an MS in
Management Information Systems and an BS in Industrial
Engineering.

3. LeasePlan
World leader in fleet management
1.8
1963Founded
175,000
1EU
reseller
6,600Employees
LP Group B.V.
Amsterdam
Present in
HQ
Worldwide customers
Investor consortium
Size of fleet
# Shareholder
million
+ +
32countries
About LeasePlan

4. Key business segments
Corporate Private
Fleet managed in one
country or across
multiple countries under
an international
umbrella agreement
• • •
Customers in a wide
variety of industries
• • •
From 26 to 1000+ cars
Private individuals
with one car for
private use
• • •
Growing part of
LeasePlan’s fleet
Small to medium
sized enterprises
• • •
Customers in a wide
variety of industries
• • •
Up to 25 cars
SMEs
About LeasePlan

5. Key facts
Global footprint
Europe
Rest of the World
89%
11%

6. End-to-end services focus
Vehicle lifecycle management
LeasePlan typically owns the car and therefore owns the value chain
Car-as-a-Service CarNext.com

7. Strategy
LeasePlan Digital
LeasePlan Digital Hub in Amsterdam
(opened in July 2017) with 230+ employees
LeasePlan Digital is the next step in our journey
following The Power of One LeasePlan1
Targets full digitisation of the value drivers
of the LeasePlan operating model
Adapts to the changing mobility market trend by offering
new mobility solutions to expand customer lifetime
2
3
4
Reorg. from Product teams to Cross-functional
Customer Journey teams5

8. 88
Online showroom where SME prospects can
• search
• select
• request a quote
• order online a vehicle
Example Customer Journey: SME Showroom

9. Traffic
Amount of visits (sessions) on
LeasePlan.com
Cost of acquiring traffic
Sales Conversion (%)
Share of submitted forms on LeasePlan.com that are
converted into signed contracts
Digital Conversion (%)
Share of consumers that visit Leasplan.com
and submit a form online
(Measure > Report > Analyze > Optimize)
Performance Optimization Cycle
LEADSONLINE
VISITS
LeasePlan.com Sales funnel (Offline)
CONTRACT
SME Showroom E2E KPI framework

10. Traffic
Amount of visits (sessions) on
LeasePlan.com
Cost of acquiring traffic
Sales Conversion (%)
Share of submitted forms on LeasePlan.com that are
converted into signed contracts
Digital Conversion (%)
Share of consumers that visit Leasplan.com
and submit a form online
ONLINE
VISITS
LeasePlan.com Sales funnel (Offline)
CONTRACT
SALES
SME Showroom E2E Data Stitching
LEADS

11. Global Commerce 2019 Projection & Strategic Levers
*All visible data is fake
Hidden data
SME Showroom – Performance Optimization Cycle enabled by Global Dashboard
Countries
Selected time
period
Countries
Countries
Countries
Selected time period
Identification of
opportunities / pain points
Ongoing performance
tracking against target
The impact of actions
triggered is measured
Further deep-dive
analysis done in other
dashboard tabs

12. *All visible data is fake
Hidden data
In-depth Customer
Journey dashboards
Most important KPIs
across Customer
Journeys
Countries
KPI 1 KPI 2 KPI 3 KPI 4 KPI 5
KPI 1 KPI 1
Digital Growth Monitor - First global multi-channel dashboard in the company

13. 13
5 learnings on our journey so far

14. Bringing a data product to life: MVP
Minimum Viable Product Minimum Valuable Product
Insights
Actions
Business value
Investment
Don’t aim for the perfect, full-scope solution from the beginning.
Picture source: https://think.design/capabilities/design-thinking-mvp/

15. Bringing a data product to life: Prioritization
Global standard vs local customization
Actionable business questions
Decision makers & budget owners
Strict prioritization is necessary, choose your “battles” wisely.

16. Bringing a data product to life: Stakeholders involvement
Requirements intake & documentation
Data viz mock-up & sign off
Data viz development
User tests
Data viz go-live
Involve stakeholders in the data viz process. Success is a partnership.

17. Bringing a data product to life: Measurement analytics for data product
What does “good” look like?
Adoption / usage KPIs & targets
Decisions taken
Business value generated

18. Bringing a data product to life: Trust
Proactive communication
Offer (temporary) solutions
Learn & improve the process
When data quality issues come up, how you handle them will shape the user perception of you & your product.

19. What’s next?

20. Advertisement Slogans
What
Happens
in
60
Seconds
if you're not paying for the product,
you are the product!
Uber owns no vehicles;
AirBnB no rooms;
Facebook no content;
and Amazon no inventory

21. Incubating
Emerging
GA
Emerging
Adoption
Evolving
Standardized
Technology Readiness vs Hype

22. 22
DATA
DATA ASSET IS
THE BASE OF
DIGITAL INTELLIGENCE

24. TelematicsEV Data
Traffic information
Weather information
Route information
Credit risk
information
Timetables
Behavior data
Social
Social media
One to one
communication
Email
App stores
Mobile app
Mobile site
.com
Search engines
Media
Digital in
store
Audience data
Voice of the
customer data
CRM data
Sales data
Marketing data
Service and
maintenance data
LeasePlan Data Ecosystem

25. Data has value when it is connected

26. 4 Vs of Big Data
VOLUME VELOCITY VARIETY VERACITY
Terabytesto exabytesofexisting
datato process
Streamingdata,millisecondsto
secondsto respond
Structured,unstructured,text,
multimedia
Uncertaintydueto datainconsistency&
incompleteness,ambiguities,latency,deception,
modelapproximations
DATA IN DOUBTDATA IN MANY FORMSDATA IN MOTIONDATA AT REST
Source: Datasciencecntral.com

27. 5th V

28. “Do business people see Data Organization as Uber?
Or the taxi company?”
Any car, any where, any time

29. ANALYTICS AT SCALE
SUPPORTING OUR GROWING BUSINESS

30. Challenges
Scalability
Structured Semi-Structured Unstructured
BatchDataVelocityReal-Time
Social Media
Sentiment
Marketing Funnel
Procurement
Predictive
Maintenance
eDWH
IoT
Video Analysis
Data scrapping
Machine Learning
Mobility as a
Service
Multi site ERP
Sales Channel Mgmt
Smart Cars
Natural Language
Processing (NLP)
Deep Learning

31. Challenges
Scalability Agility
Business – determine what questions to ask
IT – Structures the data to answer the question
IT – Delivers a platform to enable creative discovery
Business – Explores what questions could be asked
Business
Intelligence
Advanced
Analytics
Things business knows
Things business might not know
Questions business
is unaware of
Questions known to
business

32. Challenges
Scalability Agility
Data Silos
Data when used and interpreted intelligently, it becomes asset

33. Challenges
Source:Firstmark
Scalability Agility
Data Silos Adaptation

34. Cloud Analytics
Global Data Hub
Abstract
access
A single
semantic
repository
Tool
Agnostic
Architecture
Centralized,
governed
secured data
layer
Scalable
Efficient
Reliable
Managed
Cloud empowers IT
organizations to redefine
the way data services are
produced and delivered
Global Data Hub is like human heart,
pumping the data that is an
organization’s life blood throughout
Analytics at Scale in Leaseplan

35. `
NGEI – Global Data Hub Reference Architecture
DATA
ACQUISITION
DATA
SOURCES
DATA
STORE (RAW)
ANALYTICS
WAREHOUSE
DATA
SCIENCE
DATA
AS A SERVICE
DATA
CONSUMER
Next Gen Data Management (Meta-data, data quality, governance)
Meta data management, data quality, data governance as central components guarding the overall
data-asset of the corporation to allow trusted access to data for utilisation across the enterprise
Structured→Unstructured
ETL/ELTORCHESTRATIONSTREAMING
Native Extraction
No ETL Tool(s)
AWS
Kinesis
Airflow
SAP BW/4HANA +
HANA Native
Raw
Quality
Integration
Consumption
Glacier
Archive
BW/4HANA +
HANA Native
ActivPortal®
Information
Steward
NG Finance 1
NG Insurance
NG Procurement
NG Marketing
NG Sales
NG Service
NG Commerce
NG Fleet Ops
NG Supplier
Engagement
NG Policy Mgt.
NG Portals
NG Contact Center
Legacy – NOLS/
DB2/AS400 etc.
Other External
Data: Telematics,
IoT, Social feeds,
streams etc.
AWS
SageMaker
First Preference Second Preference Technologies under review

36. Example of Use Cases based on LP Data Assets in Leaseplan Digital
Predict if the car needs
maintenance before the
issue actually happens
Predict the future
repair & maintenance
cost of the car
Predict the residual
value of the car at the
end of the lease
period
Predict the future
demand of the car as a
function of the price
Predict how likely a
customer is to buy this car
Predict if the car is
damaged, at which portion
and how much will it cost to
fix it
Predictive Maintenance
Residual Value
Provide insights to
200.000+ fleet
managers all over the
world for their fleets
Customer Reporting
Car Recommendation
Car Damage Detection
Demand Forecasting &
Price Optimisation
Cost Budgeting

37. Global Data Hub is transforming Leaseplan towards Predictive Maintenance
Reactive Periodic Proactive Predictive Prescriptive
Fix
when breakdown
Scheduled
Maintenance
Eliminate defect
At Early Stage
Prevent
Failure
Analytics to
Predict Failures
Historical Real-Time

39. Top 3 Take-aways for self-service data viz & analytics success
1. Think like a product owner
2. Big data 5th V is most important : Value
3. Paradigm shift is needed to move from traditional to modern analytics platforms